
# 配置所依赖的表所处的[任务名字]及[任务所在包的位置]

# -*- coding: utf-8 -*-
from datetime import timedelta
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
from jms.time_sensor.time_after_03_00 import time_after_03_00
jms_dwd__dwd_tab_barscan_sign_realtime_flink_dt= SparkSqlOperator(
    task_id='jms_dwd__dwd_tab_barscan_sign_realtime_flink_dt',
    task_concurrency=1,
    pool_slots=2,
    master='yarn',
    execution_timeout=timedelta(minutes=30),
    email=['payne.jiang@jtexpress.com','yl_bigdata@yl-scm.com'],
    name='jms_dwd__dwd_tab_barscan_sign_realtime_flink_dt_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms/dwd/dwd_tab_barscan_sign_realtime_flink_dt/execute.sql',
    driver_cores=1 , 
    driver_memory='2G' , 
    executor_cores=2 , 
    executor_memory='2G' , 
    num_executors=2 , 
    conf={
        'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
        'spark.shuffle.service.enabled': 'true',  # 动态资源 Shuffle 服务开启
        'spark.dynamicAllocation.maxExecutors'             : 2 , 
        'spark.dynamicAllocation.cachedExecutorIdleTimeout': 30,  # 动态资源自动释放闲置 Executor 的超时时间(s)
        'spark.executor.memoryOverhead'             : '2G' , 
        'spark.hadoop.hive.exec.dynamic.partition.mode': 'nonstrict', # 动态分区
        'spark.hadoop.hive.exec.dynamic.partition': 'true',
        'spark.sql.shuffle.partitions': 2,
        'spark.sql.files.maxPartitionBytes': 268435456
    },
    yarn_queue='pro',
)
# 设置依赖
jms_dwd__dwd_tab_barscan_sign_realtime_flink_dt<< [
    time_after_03_00
]